Intelligent self-adaptive environment multi-parameter passive optical fiber sensing analysis system

Abstract

The invention belongs to the technical field of optical fiber sensing analysis, and particularly relates to an intelligent self-adaptive environment multi-parameter passive optical fiber sensing analysis system which comprises an optical fiber sensor array module, an intelligent signal processing module, a self-adaptive adjustment control module, a comprehensive monitoring alarm module and a remote control center. By fusing an optical fiber sensing technology and an intelligent algorithm, real-time monitoring and accurate analysis of environmental changes are realized, and the system has the advantages of high transmission rate and electromagnetic interference resistance, has wide application prospects in the fields of environmental monitoring, industrial production control and the like, and is suitable for popularization and application. The environment management and control difficulty in the detection period is analyzed through the environment management and control analysis module, and the inspection performance of the optical fiber sensor array module in the detection period is analyzed through the inspection influence analysis module when the environment control high-difficulty signal is generated, so that whether the influence caused by the inspection performance factor is eliminated or not is judged; management personnel can reasonably carry out follow-up management scheme planning, and the intelligent degree is high.

Description

Technical Field

[0001] The invention relates to the technical field of optical fiber sensing analysis, in particular to an intelligent self-adaptive environment multi-parameter passive optical fiber sensing analysis system. Background Art

[0002] The sensing performance of traditional fiber optic sensors is often significantly affected in complex and changing environments, which limits their wide application. However, adaptive fiber optic sensing technology responds to environmental changes by dynamically adjusting the refractive index distribution inside the fiber, showing high application potential.

[0003] Existing technologies are difficult to integrate optical fiber sensing technology and intelligent adaptive algorithms to achieve multi-parameter environmental measurement and intelligent adaptive adjustment. They are also unable to conduct accurate assessment and analysis of the difficulty of environmental control and timely early warning, which is not conducive to the subsequent environmental management plan planning and has a low degree of intelligence.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent adaptive environmental multi-parameter passive optical fiber sensing and analysis system, which solves the problem that the prior art is difficult to integrate optical fiber sensing technology and intelligent adaptive algorithm to achieve environmental multi-parameter measurement and intelligent adaptive adjustment, and is unable to gradually and accurately evaluate and analyze the difficulty of environmental control and timely warn, and has a low degree of intelligence.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An intelligent adaptive environment multi-parameter passive optical fiber sensing and analysis system, comprising an optical fiber sensor array module, an intelligent signal processing module, an adaptive adjustment control module, a comprehensive monitoring and alarm module and a remote control center;

[0008] The fiber optic sensor array module is composed of multiple fiber optic sensors of different types. It uses the nonlinear effect of optical fiber and the principle of light modulation to comprehensively monitor the environment, convert the monitoring information into optical signals and transmit them to the intelligent signal processing module.

[0009] The intelligent signal processing module receives the optical signal from the optical fiber sensor array module, and performs preprocessing operations including filtering, noise reduction and error correction, and uses intelligent algorithms to perform in-depth analysis on the processed signal to extract multi-parameter information of the environment, and sends the analysis and extraction information to the adaptive adjustment control module and the comprehensive monitoring and alarm module;

[0010] The adaptive adjustment control module extracts information based on the analysis of the intelligent signal processing module and automatically adjusts the working state of the optical fiber sensor array module to adapt to changes in different environments;

[0011] The comprehensive monitoring and alarm module stores the analysis and extraction information sent by the intelligent signal processing module, and automatically triggers the alarm mechanism when abnormal environmental parameters are monitored, and sends corresponding early warning information to the remote control center when the alarm mechanism is triggered.

[0012] Further, the fiber optic sensor array module includes a fiber grating sensor, a fiber laser sensor and a fiber coupler sensor, wherein the fiber grating sensor measures environmental parameters by monitoring the wavelength change of reflected or transmitted light;

[0013] Fiber laser sensors measure environmental parameters by monitoring changes in laser wavelength, intensity, and frequency parameters; fiber couplers measure environmental parameters by monitoring changes in coupling efficiency or splitting ratio.

[0014] Furthermore, the working process of the adaptive regulation control module includes:

[0015] Signal reception and analysis: Receive analysis and extraction information from the intelligent signal processing module, which contains detailed information on changes in relevant environmental parameters;

[0016] Strategy formulation: Based on the received analysis and extraction information, a corresponding adjustment strategy is formulated, wherein the formulated adjustment strategy aims to optimize the sensing performance by adjusting the working parameters of the optical fiber sensor array module to adapt to the current environment;

[0017] Parameter adjustment: performing parameter adjustment operations, wherein the adjustment operations include changing the length of the optical fiber, adjusting the refractive index distribution of the optical fiber, and optimizing the coupling efficiency of the optical fiber sensor, so as to improve the sensitivity and response speed of the optical fiber sensor array module to changes in environmental parameters;

[0018] Feedback and optimization: During the parameter adjustment process, feedback signals from the fiber optic sensor array module are continuously collected to evaluate the adjustment effect. If the adjustment effect is not ideal, the strategy is readjusted and a new round of adjustment operations is performed.

[0019] Furthermore, the comprehensive monitoring and alarm module is communicatively connected to the environmental control and analysis module. When the alarm mechanism is triggered, the comprehensive monitoring and alarm module sends corresponding warning information to the environmental control and analysis module. The environmental control and analysis module is used to set a detection period, analyze the difficulty of environmental control during the detection period, and generate an environmental control high-difficulty signal or an environmental control low-difficulty signal through analysis, and send the environmental control high-difficulty signal or the environmental control low-difficulty signal to the remote control center.

[0020] Furthermore, the specific analysis process of the environmental control analysis module includes:

[0021] The number of times the warning information is generated during the detection period is obtained and marked as the environmental warning value, and the generation time of all warning information is collected. The time difference between the generation times of two adjacent groups of warning information is calculated to obtain the warning interval duration, and the warning interval duration is numerically compared with the preset warning interval duration threshold. If the warning interval duration does not exceed the preset warning interval duration threshold, the corresponding warning interval duration is marked as the warning abnormality interval duration;

[0022] The number of warning intervals during the detection period is obtained and marked as the warning interval value, and the average of all warning intervals during the detection period is calculated to obtain the warning interval detection value. The environmental warning value, the warning interval value and the warning interval detection value are numerically calculated to obtain the environmental control preliminary analysis value. The environmental control preliminary analysis value is numerically compared with the preset environmental control preliminary analysis threshold. If the environmental control preliminary analysis value exceeds the preset environmental control preliminary analysis threshold, an environmental control high difficulty signal is generated.

[0023] Furthermore, if the environmental control preliminary analysis value does not exceed the preset environmental control preliminary analysis threshold, all environmental parameters that need to be monitored are obtained, and the corresponding environmental parameters are marked as target parameters i, and i is a natural number greater than 1. Analysis is performed to determine whether there are non-controllable parameters during the detection period. If there are non-controllable parameters, an environmental control high difficulty signal is generated; if there are no non-controllable parameters, an environmental integrated analysis is performed.

[0024] Furthermore, the specific analysis process for determining whether there are non-controllable parameters during the detection period is as follows:

[0025] All warning information generated during the detection period is obtained. Based on all the warning information, the total number of times the target parameter i is judged as an abnormal environmental parameter during the detection period is collected and marked as a parameter abnormal judgment value. The parameter abnormal judgment value is numerically compared with the corresponding preset parameter abnormal judgment threshold. If the parameter abnormal judgment value exceeds the corresponding preset parameter abnormal judgment threshold, the target parameter i is marked as a non-abnormal control parameter.

[0026] Furthermore, the specific analysis process of environmental integration analysis is as follows:

[0027] The ratio of the parameter deviation judgment value of the target parameter i to the corresponding preset parameter deviation judgment threshold is marked as the parameter deviation detection value, and each environmental parameter is set in advance to correspond to a set of preset influence weight values, and the product of the parameter deviation detection value of the target parameter i and the corresponding preset influence weight value is marked as the parameter deviation table value, and the parameter deviation table values ​​of all environmental parameters that need to be monitored are summed and calculated to obtain the parameter integration value;

[0028] The environmental control comprehensive evaluation value is obtained by numerically calculating the parameter integration value and the environmental control preliminary analysis value, and the environmental control comprehensive evaluation value is numerically compared with the preset environmental control comprehensive evaluation threshold. If the environmental control comprehensive evaluation value exceeds the preset environmental control comprehensive evaluation threshold, an environmental control high difficulty signal is generated; if the environmental control comprehensive evaluation value does not exceed the preset environmental control comprehensive evaluation threshold, an environmental control low difficulty signal is generated.

[0029] Furthermore, the environmental control analysis module is communicated with the inspection impact analysis module. The environmental control analysis module sends the environmental control high difficulty signal to the inspection impact analysis module. The inspection impact analysis module analyzes the inspection performance of the optical fiber sensor array module during the detection period, generates an inspection high impact signal or an inspection low impact signal through analysis, and sends the inspection high impact signal or the inspection low impact signal to the remote control center.

[0030] Furthermore, the specific analysis process of the impact analysis module is as follows:

[0031] The time of inspection and maintenance of the optical fiber sensor array module during the detection period is collected and marked as the detection time, the interval between two adjacent detection moments is marked as the detection interval time, the detection interval time is numerically compared with the preset detection interval time threshold, and if the detection interval time exceeds the preset detection interval time threshold, the corresponding detection interval time is marked as the detection error time;

[0032] The number of detection time periods in the detection period is obtained and marked as the detection value, and the average of all the detection time periods exceeding the preset detection time threshold is marked as the detection timeout value, and the detection time period with the largest value exceeding the preset detection time threshold is marked as the detection over-amplitude value;

[0033] The inspection influence coefficient is obtained by numerically calculating the inspection condition value, the inspection timeout value and the inspection excess amplitude value; the inspection influence coefficient is numerically compared with the preset inspection influence coefficient threshold. If the inspection influence coefficient exceeds the preset inspection influence coefficient threshold, a high inspection influence signal is generated; if the inspection influence coefficient does not exceed the preset inspection influence coefficient threshold, a low inspection influence signal is generated.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1. In the present invention, the optical fiber sensor array module utilizes the nonlinear effect of optical fiber and the principle of optical modulation to comprehensively monitor the environment, the intelligent signal processing module performs preprocessing operations on the optical signal and extracts multi-parameter information of the environment, and the adaptive adjustment control module automatically adjusts the working state of the optical fiber sensor array module according to the analysis and extraction information to adapt to changes in different environments, and sends corresponding early warning information to the remote control center when abnormal environmental parameters are monitored, thereby realizing real-time monitoring and accurate analysis of environmental changes, and having broad application prospects in the fields of environmental monitoring, industrial production control, etc.

[0036] 2. In the present invention, the difficulty of environmental control during the detection period is analyzed through the environmental control analysis module to generate an environmental control high-difficulty signal or an environmental control low-difficulty signal. When the environmental control high-difficulty signal is generated, the inspection performance of the optical fiber sensor array module during the detection period is analyzed through the inspection impact analysis module, which is conducive to the management personnel to reasonably plan the subsequent environmental management plan, and has a high degree of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0038] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0039] Figure 2 This is a system block diagram of Embodiment 2 and Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Embodiment 1: Figure 1 As shown, the present invention proposes an intelligent adaptive environment multi-parameter passive optical fiber sensing and analysis system, including an optical fiber sensor array module, an intelligent signal processing module, an adaptive adjustment control module, a comprehensive monitoring and alarm module and a remote control center;

[0042] The optical fiber sensor array module is composed of multiple optical fiber sensors of different types. It is passive and does not require external power supply, which improves the stability and safety of the system. It uses the nonlinear effect of optical fiber and the principle of optical modulation to comprehensively monitor the environment, and converts the monitoring information into optical signals and transmits them to the intelligent signal processing module. It should be noted that the optical fiber sensor array module includes optical fiber grating sensors, optical fiber laser sensors and optical fiber coupler sensors.

[0043] Fiber Bragg grating is a structure formed by introducing periodic refractive index changes in optical fiber. When the optical signal passes through the fiber Bragg grating, light of a specific wavelength will be reflected or transmitted. This wavelength dependence enables the fiber Bragg grating to be used as a sensor. The fiber Bragg grating sensor measures environmental parameters by monitoring the wavelength changes of reflected or transmitted light. It can measure changes in physical quantities such as ambient temperature and pressure.

[0044] Fiber lasers use optical fibers as gain media and waveguides, and generate laser light by exciting rare earth ions or semiconductor materials in the optical fibers with pump light. Fiber laser sensors measure environmental parameters by monitoring changes in laser wavelength, intensity, frequency and other parameters. For example, changes in ambient temperature can be inferred by measuring changes in laser wavelength.

[0045] A fiber optic coupler sensor is a device that couples or splits the optical signals of two or more optical fibers. In sensor applications, fiber optic coupler sensors measure environmental parameters by monitoring changes in coupling efficiency or splitting ratio. For example, when a fiber optic coupler sensor is subjected to external pressure or temperature changes, its coupling efficiency or splitting ratio will change, thereby achieving the measurement of these parameters.

[0046] The intelligent signal processing module receives the optical signal from the optical fiber sensor array module, and performs preprocessing operations including filtering, noise reduction and error correction, and uses intelligent algorithms to perform in-depth analysis on the processed signal to extract environmental multi-parameter information (including temperature, pressure, vibration and humidity, etc.), and sends the analyzed and extracted information to the adaptive adjustment control module and the comprehensive monitoring and alarm module;

[0047] It should be noted that filtering technology (such as low-pass, high-pass, band-pass filters, etc.) is used to remove unnecessary frequency components, and noise reduction algorithms (such as wavelet transform, adaptive filtering, etc.) are applied to further reduce noise and improve the signal-to-noise ratio of the signal. The signal is corrected through built-in error correction algorithms (such as polynomial fitting, table lookup, etc.) to eliminate or reduce these errors and ensure the accuracy of the signal.

[0048] In addition, the intelligent signal processing module integrates deep learning technology, which is a powerful machine learning method that can automatically learn complex feature representations from data. By training deep learning models (such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), it can identify and extract feature information related to parameters such as ambient temperature, pressure, vibration, and humidity in the signal.

[0049] In addition to the deep learning model, the intelligent signal processing module also includes traditional neural networks (such as BP neural network, radial basis function network, etc.), which are used to perform further classification, regression and other tasks on the processed signals. These neural networks can simulate the working mode of human brain neurons, perform nonlinear processing on signals, and improve the accuracy and robustness of parameter extraction.

[0050] The adaptive adjustment control module extracts information based on the analysis of the intelligent signal processing module and automatically adjusts the working state of the optical fiber sensor array module to adapt to changes in different environments. The working process of the adaptive adjustment control module is as follows:

[0051] Signal reception and analysis: Receive analysis and extraction information from the intelligent signal processing module. The analysis and extraction information contains detailed information about changes in environmental parameters, such as specific values ​​of temperature, pressure, vibration, etc. and their changing trends;

[0052] Strategy formulation: Based on the received analysis and extraction information, a corresponding adjustment strategy is formulated, wherein the formulated adjustment strategy aims to optimize the sensing performance by adjusting the working parameters of the optical fiber sensor array module to better adapt to the current environment;

[0053] Parameter adjustment: performing parameter adjustment operations, wherein the adjustment operations include changing the length of the optical fiber (by stretching or compressing the optical fiber), adjusting the refractive index distribution of the optical fiber (by changing the stress or temperature distribution inside the optical fiber), optimizing the coupling efficiency of the optical fiber sensor, etc. These adjustment operations are intended to improve the sensitivity and response speed of the optical fiber sensor array module to changes in environmental parameters;

[0054] Feedback and optimization: During the parameter adjustment process, feedback signals from the fiber optic sensor array module are continuously collected to evaluate the adjustment effect. If the adjustment effect is not ideal, the strategy is readjusted and a new round of adjustment operations is performed until the optimal sensing performance is achieved.

[0055] The comprehensive monitoring and alarm module stores the analysis and extraction information sent by the intelligent signal processing module, and automatically triggers the alarm mechanism when abnormal environmental parameters are monitored. When the alarm mechanism is triggered, it sends corresponding early warning information to the remote control center so that management personnel can take timely response measures.

[0056] The present invention realizes real-time monitoring and precise analysis of environmental changes by integrating optical fiber sensing technology and intelligent algorithms. It has the advantages of fast transmission rate and resistance to electromagnetic interference. It has broad application prospects in environmental monitoring, industrial production control and other fields, and can significantly improve the monitoring efficiency and accuracy in related fields.

[0057] Embodiment 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the comprehensive monitoring and alarm module is communicatively connected to the environmental control and analysis module. When the alarm mechanism is triggered, the comprehensive monitoring and alarm module sends the corresponding warning information to the environmental control and analysis module. The environmental control and analysis module is used to set the detection period. Preferably, the detection period is fifteen days; the control difficulty of the environment during the detection period is analyzed, and a high-difficulty signal of environmental control or a low-difficulty signal of environmental control is generated through analysis;

[0058] And send the high-difficulty signal of environmental control or the low-difficulty signal of environmental control to the remote control center. When the remote control center receives the high-difficulty signal of environmental control, it reminds the management personnel to conduct cause investigation and analysis, and strengthen environmental supervision in the future, which is conducive to subsequent management planning and has a high degree of intelligence. The specific analysis process of the environmental control analysis module is as follows:

[0059] The number of times the warning information is generated during the detection period is obtained and marked as the environmental warning value, and the generation time of all warning information is collected. The time difference between the generation times of two adjacent groups of warning information is calculated to obtain the warning interval duration, and the warning interval duration is numerically compared with the preset warning interval duration threshold. If the warning interval duration does not exceed the preset warning interval duration threshold, the corresponding warning interval duration is marked as the warning abnormality interval duration;

[0060] The number of warning intervals during the detection period is obtained and marked as the warning interval detection value, and the average of all warning intervals during the detection period is calculated to obtain the warning interval detection value;

[0061] By formula The environmental warning value WN, the warning abnormal interval detection value WL and the warning interval detection value WS are numerically calculated to obtain the environmental control preliminary analysis value WP; wherein, q1, q2, q3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the environmental control preliminary analysis value WP is, the worse the environmental performance during the detection period is, and the greater the difficulty of environmental management is.

[0062] The environmental control preliminary analysis value WP is numerically compared with the preset environmental control preliminary analysis threshold. If the environmental control preliminary analysis value WP exceeds the preset environmental control preliminary analysis threshold, it indicates that the environmental performance during the detection period is poor and the environmental management difficulty is initially large, then a high difficulty signal for environmental control is generated.

[0063] Further, if the environmental control preliminary analysis value does not exceed the preset environmental control preliminary analysis threshold, all environmental parameters that need to be monitored are obtained, and the corresponding environmental parameters are marked as target parameters i, and i is a natural number greater than 1. All warning information generated during the detection period is obtained, and the total number of times the target parameter i is judged as an abnormal environmental parameter during the detection period is collected based on all warning information and marked as a parameter abnormal judgment value, and the parameter abnormal judgment value is numerically compared with the corresponding preset parameter abnormal judgment threshold. If the parameter abnormal judgment value exceeds the corresponding preset parameter abnormal judgment threshold, indicating that the target parameter i is frequently abnormal during the detection period, the target parameter i is marked as a non-abnormal control parameter;

[0064] If there are non-controllable parameters, indicating that the environmental management is difficult, a high-difficulty signal for environmental control is generated; if there are no non-controllable parameters, an environmental integration analysis is performed, specifically: the ratio of the parameter difference judgment value of the target parameter i to the corresponding preset parameter difference judgment threshold is marked as the parameter difference detection value, and each environmental parameter is set in advance to correspond to a set of preset impact weight values. It should be noted that the values ​​of the preset impact weight values ​​are all positive numbers, and the greater the adverse impact of the corresponding environmental parameter on the environment, the greater the value of the preset impact weight value adapted to it;

[0065] The product of the parameter anomaly detection value of the target parameter i and the corresponding preset influence weight value is marked as the parameter anomaly value, and the parameter anomaly values ​​of all environmental parameters that need to be monitored are summed up to obtain the parameter integration value;

[0066] The parameter integration value YL and the environmental control preliminary analysis value WP are numerically calculated by the formula YP=ku1*YL+ku2*WP to obtain the environmental control comprehensive evaluation value YP; wherein ku1 and ku2 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the environmental control comprehensive evaluation value YP is, the greater the difficulty of environmental control during the detection period is.

[0067] The environmental control comprehensive evaluation value YP is numerically compared with the preset environmental control comprehensive evaluation threshold. If the environmental control comprehensive evaluation value YP exceeds the preset environmental control comprehensive evaluation threshold, indicating that the difficulty of environmental control during the detection period is generally large, then an environmental control high difficulty signal is generated; if the environmental control comprehensive evaluation value YP does not exceed the preset environmental control comprehensive evaluation threshold, indicating that the difficulty of environmental control during the detection period is generally small, then an environmental control low difficulty signal is generated.

[0068] Embodiment 3: Figure 2As shown, the difference between this embodiment and the first and second embodiments is that the environment control analysis module is connected to the inspection impact analysis module in communication, and the environment control analysis module sends the high difficulty signal of environment control to the inspection impact analysis module. When the inspection impact analysis module receives the high difficulty signal of environment control, it analyzes the inspection performance of the optical fiber sensor array module during the detection period, and generates a high impact signal of inspection or a low impact signal of inspection through analysis.

[0069] And the inspection high impact signal or inspection low impact signal is sent to the remote control center, which can reasonably analyze the impact of inspection performance when it is judged that the environmental control is difficult, so as to judge whether to eliminate the impact of inspection performance factors, which is conducive to the management personnel to reasonably plan the subsequent management plan, and has a high degree of intelligence; the specific analysis process of the inspection impact analysis module is as follows:

[0070] The time when the optical fiber sensor array module is inspected and maintained during the detection period (i.e., the optical fiber sensor array module is inspected and the accuracy of its detection results is tested, and corresponding improvement measures are taken based on the detection results) is collected and marked as the detection time, the interval between two adjacent groups of detection moments is marked as the detection interval time, the detection interval time is numerically compared with the preset detection interval time threshold, and if the detection interval time exceeds the preset detection interval time threshold, the corresponding detection interval time is marked as the detection error time;

[0071] The number of detection time periods in the detection period is obtained and marked as the detection value, and the average of all the detection time periods exceeding the preset detection time threshold is marked as the detection timeout value, and the detection time period with the largest value exceeding the preset detection time threshold is marked as the detection over-amplitude value;

[0072] The inspection influence coefficient XP is obtained by numerically calculating the inspection condition value XN, the inspection timeout value XW and the inspection over-amplitude value XK through the formula XP=ey1*XN+(ey2*XW+ey3*XK) / 2; wherein ey1, ey2 and ey3 are preset proportional coefficients, ey1>ey2>ey3>0; and the larger the value of the inspection influence coefficient XP, the worse the inspection performance of the optical fiber sensor array module during the detection period, the greater the risk of error in the accuracy of the monitoring result of the optical fiber sensor array module, and the greater the probability of generating a high-difficulty signal for environmental control due to monitoring errors;

[0073] The inspection influence coefficient XP is numerically compared with the preset inspection influence coefficient threshold. If the inspection influence coefficient XP exceeds the preset inspection influence coefficient threshold, it indicates that the inspection performance of the optical fiber sensor array module during the detection period is poor, and the probability of generating a high-difficulty signal of environmental control due to the monitoring error of the optical fiber sensor array module is high, and an inspection high-impact signal is generated;

[0074] If the inspection influence coefficient XP does not exceed the preset inspection influence coefficient threshold, it indicates that the inspection performance of the optical fiber sensor array module during the detection period is good, and the probability of generating a high-difficulty environmental control signal due to the monitoring error of the optical fiber sensor array module is small, then a low-impact inspection signal is generated.

[0075] The working principle of the present invention is as follows: when in use, the optical fiber sensor array module utilizes the nonlinear effect of the optical fiber and the principle of optical modulation to comprehensively monitor the environment, the intelligent signal processing module performs preprocessing operations on the optical signal and extracts the multi-parameter information of the environment, the adaptive adjustment control module automatically adjusts the working state of the optical fiber sensor array module according to the analysis and extraction information to adapt to the changes in different environments, and when abnormal environmental parameters are monitored, the alarm mechanism is automatically triggered by the comprehensive monitoring and alarm module to send corresponding early warning information to the remote control center, thereby realizing real-time monitoring and accurate analysis of environmental changes, having the advantages of fast transmission rate and anti-electromagnetic interference, etc., and having broad application prospects in the fields of environmental monitoring, industrial production control, etc., and the environmental control and management analysis module analyzes the control difficulty of the environment during the detection period to generate an environmental control high-difficulty signal or an environmental control low-difficulty signal, and when generating an environmental control high-difficulty signal, the inspection performance of the optical fiber sensor array module during the detection period is analyzed by the inspection influence analysis module, so as to determine whether the influence of the inspection performance factor is eliminated, which is conducive to the management personnel to reasonably plan the subsequent management plan, and has a high degree of intelligence.

[0076] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system, It is characterized in that It includes optical fiber sensor array module, intelligent signal processing module, adaptive adjustment control module, comprehensive monitoring and alarm module and remote control center; The fiber optic sensor array module is composed of multiple fiber optic sensors of different types. It uses the nonlinear effect of optical fiber and the principle of light modulation to comprehensively monitor the environment, convert the monitoring information into optical signals and transmit them to the intelligent signal processing module. The intelligent signal processing module receives the optical signal from the optical fiber sensor array module, performs preprocessing operations, and uses intelligent algorithms to perform in-depth analysis on the processed signal to extract multi-parameter information of the environment, and sends the analyzed and extracted information to the adaptive adjustment control module and the comprehensive monitoring and alarm module; The adaptive adjustment control module extracts information based on the analysis of the intelligent signal processing module and automatically adjusts the working state of the optical fiber sensor array module to adapt to changes in different environments; The comprehensive monitoring and alarm module stores the analysis and extraction information sent by the intelligent signal processing module, and automatically triggers the alarm mechanism when abnormal environmental parameters are monitored, and sends corresponding early warning information to the remote control center when the alarm mechanism is triggered.

2. According to claim 1, an intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system, It is characterized in that The fiber optic sensor array module includes a fiber grating sensor, a fiber laser sensor and a fiber coupler sensor, wherein the fiber grating sensor measures environmental parameters by monitoring the wavelength change of reflected or transmitted light; Fiber laser sensors measure environmental parameters by monitoring changes in laser wavelength, intensity, and frequency parameters; fiber couplers measure environmental parameters by monitoring changes in coupling efficiency or splitting ratio.

3. According to claim 1, an intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system, It is characterized in that The working process of the adaptive regulation control module includes: Signal reception and analysis: receiving and analyzing information from the intelligent signal processing module; Strategy formulation: Based on the analysis and extraction information received, formulate corresponding adjustment strategies; Parameter adjustment: perform parameter adjustment operations to improve the sensitivity and response speed of the fiber optic sensor array module to changes in environmental parameters; Feedback and optimization: During the parameter adjustment process, feedback signals from the fiber optic sensor array module are continuously collected to evaluate the adjustment effect. If the adjustment effect is not ideal, the strategy is readjusted and a new round of adjustment operations is performed.

4. The intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system according to claim 1, It is characterized in that The comprehensive monitoring and alarm module is communicatively connected to the environmental control and analysis module. When the alarm mechanism is triggered, the comprehensive monitoring and alarm module sends corresponding warning information to the environmental control and analysis module. The environmental control and analysis module is used to set the detection period, analyze the control difficulty of the environment during the detection period, and generate an environmental control high-difficulty signal or an environmental control low-difficulty signal through analysis, and send the environmental control high-difficulty signal or the environmental control low-difficulty signal to the remote control center.

5. The intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system according to claim 4, It is characterized in that The specific analysis process of the environmental control analysis module includes: The number of times the warning information is generated during the detection period is obtained and marked as the environmental warning value, and the generation time of all warning information is collected. The time difference between the generation times of two adjacent groups of warning information is calculated to obtain the warning interval duration, and the warning interval duration is numerically compared with the preset warning interval duration threshold. If the warning interval duration does not exceed the preset warning interval duration threshold, the corresponding warning interval duration is marked as the warning abnormality interval duration; The number of warning intervals during the detection period is obtained and marked as the warning interval detection value, and the average of all warning intervals during the detection period is calculated to obtain the warning interval detection value. The environmental warning value, the warning interval detection value and the warning interval detection value are numerically calculated to obtain the environmental control preliminary analysis value. If the environmental control preliminary analysis value exceeds the preset environmental control preliminary analysis threshold, an environmental control high difficulty signal is generated.

6. The intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system according to claim 5, It is characterized in that If the environmental control preliminary analysis value does not exceed the preset environmental control preliminary analysis threshold, all environmental parameters that need to be monitored are obtained, and the corresponding environmental parameters are marked as target parameters i, where i is a natural number greater than 1. Through analysis, it is determined whether there are non-controllable parameters during the detection period. If there are non-controllable parameters, a high-difficulty signal for environmental control is generated; If there are no uncontrollable parameters, an environmental integration analysis is performed.

7. The intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system according to claim 6, It is characterized in that The specific analysis process to determine whether there are uncontrollable parameters during the detection period is as follows: All warning information generated during the detection period is obtained. Based on all warning information, the total number of times the target parameter i is judged as an abnormal environmental parameter during the detection period is collected and marked as the parameter abnormal judgment value. If the parameter abnormal judgment value exceeds the corresponding preset parameter abnormal judgment threshold, the target parameter i is marked as a non-abnormal control parameter.

8. The intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system according to claim 6, It is characterized in that The specific analysis process of environmental integration analysis is as follows: The ratio of the parameter deviation judgment value of the target parameter i to the corresponding preset parameter deviation judgment threshold is marked as the parameter deviation detection value, and each environmental parameter is set in advance to correspond to a set of preset influence weight values, and the product of the parameter deviation detection value of the target parameter i and the corresponding preset influence weight value is marked as the parameter deviation table value, and the parameter deviation table values ​​of all environmental parameters that need to be monitored are summed and calculated to obtain the parameter integration value; The environmental control comprehensive evaluation value is obtained by numerically calculating the parameter integration value and the environmental control preliminary analysis value. If the environmental control comprehensive evaluation value exceeds the preset environmental control comprehensive evaluation threshold, an environmental control high difficulty signal is generated; if the environmental control comprehensive evaluation value does not exceed the preset environmental control comprehensive evaluation threshold, an environmental control low difficulty signal is generated.

9. The intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system according to claim 1, It is characterized in that The environmental control analysis module is communicated with the inspection impact analysis module. The environmental control analysis module sends the environmental control high difficulty signal to the inspection impact analysis module. The inspection impact analysis module analyzes the inspection performance of the optical fiber sensor array module during the detection period, generates an inspection high impact signal or an inspection low impact signal through analysis, and sends the inspection high impact signal or the inspection low impact signal to the remote control center.

10. The intelligent adaptive environment multi-parameter passive optical fiber sensing analysis system according to claim 9, It is characterized in that The specific analysis process of the impact analysis module is as follows: The time of inspection and maintenance of the optical fiber sensor array module during the detection period is collected and marked as the detection time, and the interval between two adjacent detection time groups is marked as the detection interval time. If the detection interval time exceeds the preset detection interval time threshold, the corresponding detection interval time is marked as the detection error time. The number of detection time periods in the detection period is obtained and marked as the detection value, and the average of all the detection time periods exceeding the preset detection time threshold is marked as the detection timeout value, and the detection time period with the largest value exceeding the preset detection time threshold is marked as the detection over-amplitude value; The inspection influence coefficient is obtained by numerically calculating the inspection condition value, the inspection timeout value and the inspection excess amplitude value. If the inspection influence coefficient exceeds the preset inspection influence coefficient threshold, a high inspection influence signal is generated; if the inspection influence coefficient does not exceed the preset inspection influence coefficient threshold, a low inspection influence signal is generated.

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